#!/usr/bin/env python3
from pyprove import expres, log
experiment = {
"bid": "mizar40/10k",
#"pids": ["mzr01","aim01","tptp01"],
"pids": open("eval").read().strip().split("\n"),
"limit": "T5",
"cores": 60,
"eargs": "--training-examples=3 -s --free-numbers"
}
log.start("Evaluation:", experiment)
experiment["results"] = expres.benchmarks.eval(**experiment)
#expres.dump.processed(**experiment)
expres.dump.solved(**experiment)
'reg_lambda': 0,
'random_state': 42,
'objective': 'binary',
'min_child_samples': 40,
#'max_depth': 16,
'max_depth': 20,
}
settings = {
"bid": "mizar40/all",
"pids": ["mzr02"],
"ref": "mzr02",
"limit": "G20000-T100",
"cores": 60,
"version": "VHSLCAXPh",
#"version" : "VHSLCXPh",
"eargs": "--training-examples=3 -s --free-numbers",
"hashing": 2**15,
"ramdisk": "/dev/shm/yan",
"learner": learn.LightGBM(**learning)
}
log.start("Starting Enigma experiments:", settings)
model = models.name(**settings)
models.loop(model, settings, nick="loop00")
expres.dump.processed(**settings)
expres.dump.solved(**settings)
"cores":
60,
"version":
"VHSLCAXPh",
#"eargs" : "--training-examples=3 -s --free-numbers",
"hashing":
2**15,
#"ramdisk": "/dev/shm/yan",
"gzip":
False,
"learner":
learn.XGBoost(**learning)
}
models.check(settings)
log.start("Building XGB models:", settings)
model = models.name(**settings)
rkeys = [(settings["bid"], pid, problem, settings["limit"])
for pid in settings["pids"]
for problem in expres.benchmarks.problems(settings["bid"])]
if not models.make(model, rkeys, settings):
raise Exception("Enigma: FAILED: Building model %s" % model)
efun = settings["learner"].efun()
new.append(
protos.solo(settings["pids"][0],
model,
mult=0,
noinit=True,
efun=efun))
new.append(
protos.coop(settings["pids"][0],
#!/usr/bin/env python3
from pyprove import expres, log
experiment = {
"bid": "mizar40/all",
"cores": 68,
}
log.start("CNFize Benchmark(s)", experiment)
expres.benchmarks.cnfize(**experiment)